Remote Reinforcement Learning Systems Engineer

Bright Vision Technologies

Bellevue (WA)

On-site

USD 100,000 - 150,000

Full time

9 days ago

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Job summary

Bright Vision Technologies is seeking an AI Learning Systems Engineer to design, train, and deploy RL-based systems for high-impact decision problems. The role emphasizes taking RL solutions from research to production with emphasis on stability, safety, and ongoing improvement.

The ideal candidate will have 6+ years in RL research/engineering, strong Python and modern DL frameworks, experience with RL libraries, and proven ability to train neural policies on GPU clusters.

Qualifications

  • Master’s or PhD in CS/ML or related field or equivalent experience.
  • 6+ years of RL research and engineering experience.
  • Strong Python and modern deep learning frameworks.
  • Hands-on experience with at least one major RL library or in-house RL stack.
  • Experience training neural network policies on GPU clusters.
  • Strong written and verbal communication skills; track record of RL work.

Responsibilities

  • Design, train, and deploy RL-based systems for high-impact decision problems.
  • Take RL solutions from research to production with emphasis on stability and safety.
  • Prototype, evaluate, and optimize RL policies at scale.
  • Collaborate with ML researchers and software engineers to deliver production-ready solutions.

Skills

Python
Deep learning
Reinforcement learning
GPU clusters
Communication
RL publications

Education

Master’s/PhD in CS/ML or related

Tools

RL library / in-house RL stack

Job description

Bright Vision Technologies is seeking an AI Learning Systems Engineer to design, train, and deploy RL-based systems for high-impact decision problems. The role emphasizes taking RL solutions from research to production with emphasis on stability, safety, and ongoing improvement.

The ideal candidate will have 6+ years in RL research/engineering, strong Python and modern DL frameworks, experience with RL libraries, and proven ability to train neural policies on GPU clusters.

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